Core coverage
Retrieve daily prices for major currency pairs
Research use
Add FX variables to cross-market research
Extended capability
Use one interface alongside stocks, indices and flows
REST API · PYTHON SDK · MCP
One request into your workflow
Every endpoint uses consistent authentication, security symbols and JSON responses, with REST API, Python SDK and MCP access available.
# pip install quantcoda import quantcoda as qc qc.set_token("qc_live_your_key") df = qc.fx_daily(symbol="USDCNH.FXCM", start_date="20260101")
What this China market dataset includes
FX is exposed through 1 documented endpoint. Each response preserves exchange-qualified security symbols, explicit trading or reporting dates and stable field meanings so that the same query can be reviewed in code, a backtest or an agent workflow.
FX daily bars (default USDCNH)
Typical filters: symbol, start_date, end_date, trade_date
CONSISTENT INPUTS
Symbols and dates that remain explicit
China stock symbols include their exchange suffix, such as 600519.SH, 000001.SZ or 430047.BJ. Calendar dates use YYYYMMDD; financial endpoints distinguish announcement dates from reporting periods.
RESEARCH OUTPUT
JSON for APIs, DataFrames for Python
REST responses use typed JSON values. The official Python SDK converts the same records into pandas DataFrames, while MCP exposes the same authenticated data contract to compatible AI clients.
FIELD-LEVEL DOCS
Inspect meaning before modelling
The documentation lists request parameters, response columns, units and plan requirements for every endpoint. Missing values remain explicit rather than being silently imputed by the API.